Today, there is significant interest in developing the prediction of the life consumption of individual components in a machine, in particular in machines with moving parts. By improving the accuracy of such methods and systems, the applied safety limits may be reduced, and unnecessary replacement of components may be avoided. When applied to an entire fleet (e.g., a military aircraft fleet) the cost savings may be significant as well as allowing for an increased operational lifetime. Furthermore, in the unusual event that conventional methods are too optimistic, refined methods may avoid failure of components, thus avoiding uncalculated stops in operation or even more importantly accidents.
Examples of interesting applications where improved life consumption predictions may be useful include aircrafts, gas/steam turbines, trucks, loaders, nuclear plants and wind turbines.
A conventional method for predicting the life consumption of a component in a machine is to measure one or a combination of the usage/run time, distance or count the number of cycles of a predefined load session or a conservative load session. A load session is the time when the machine is in operation, for example for an aircraft a load session may be defined as flying from point A to point B with a predefined rotor speed variation.
In the field of aircrafts, the life consumption of an engine is sometimes determined by making a “simplified” cycle count, focusing on the usage of a specific engine component. There are also available more specific and at least in some sense more reliable methods where, e.g., ELCF (equivalent low cycle fatigue) cycles for the specific, for example, engine component is determined. Such ELCF cycles may for example be calculated based on the high pressure rotor speed of an aircraft jet engine recorded during a load session. The cycles may be determined by the number of times the high pressure rotor speed exceeds certain selected and predefined rotor speeds. Furthermore, to calculate the ELCF cycles, scale factors are determined for the cycles based on predetermined load sessions. However, a major drawback with the ELCF cycles is that the prediction of life consumption will have errors if the actual load sessions experienced by an individual differs significantly from the predetermined load sessions, which the scale factors are based upon.
In order to more accurately determine the life consumption of an, e.g., engine, the life consumption for relevant components in the engine must be determined. In order to determine the life consumption of specific components, more detailed knowledge of conditions in separate parts of the engine is required.
In EP2390742, an improved method of approximating engine life usage is described, using a system with a set of simplified usage counters. The set of simplified usage counters, severity counters (SC), is used to estimate the damage of an aircraft engine during use. The severity counters are functions relating to a specific engine parameter, such as high pressure shaft speed, torque, exhaust gas temperature in combination with engine flight time. The same severity counter could be used to approximate the damage in several components of the engine. Correlation between the counters and the damage in the engine is calibrated by an exact calculation of the accumulated damage. To slightly improve the approximations of the damage, Monte Carlo simulations of a fleet of engines are used as a statistical approach to avoid always assuming the worst-case damage.
As demands for cost efficiency have increased, the interest in finding a better model for predicting life consumption has also increased. The conventional methods do not take all significant load cycles into consideration.
For example, the method of counting ELCF-cycles only considers one engine parameter of the entire engine while the life consumption of the critical components in an engine or machine may vary depending on which loads are most important for the life consumption of respective component. The method presented in EP2390742 fails to convey a refined method for predicting life consumption with regards to damages depending on all the different load sessions experienced by each individual.
Hence, there is a need for an improved more accurate method for predicting the life consumption of components in a machine based on all actual load sessions with enhanced focus on both safety and cost-efficient aspects.